Mimicing Shiny with Quarto + bslib
It was discussed in the last COCA meeting that we need some sort of static display options as an alternative to the shiny app.
An alternative display option that mimics 80% of the functionality is to blend web-based UI displays from {bslib} with some light interactivity that can be hosted as a static webpage.
Here are the components that I’m thinking of:
1. bslib for cards: these create a modern look that would be consistent with shiny. Use these to hold and frame content.
2. crosstalk + ggplot: These two packages together can add interactivity to a static page. If we’re smart about the data we need, we can mimic the shiny app functionality but keep it light.
3. Observable.js, there is also an option to build plots/tables/charts with observable for interactivity as well
Another interesting but time consuming path would be to try out observable framework: https://observablehq.com/framework/
Content Goals
The following lines are notes from Kat:
* Make a heading on the front baseline page about what this page is generally about, why am I here. Heading and two sentences
* Could not publish yet
* Could just make a mini app with two maps of change with different temp thresholds
* Be specific on what does say and doesn’t say (e.g. stock recovery status, ecological interactions)
* Explaining what a model does and doesn’t do - need a read me on the app
* Explaining biomass - better connect to habitat. Habitat suitability that support biomass or something similar. habitat potential/suitability
* Baseline and future maps probably most useful
Content Cards: bslib
bslib uses the newest bootstrap ui library to generate modern html containers for storing content. The major design element is the content “card”.
Interactive Data: crosstalk
Crosstalk adds reactivity to static pages along users to select and filter data. Brushing can also be used to highlight data across plots highlighting different dimensions of the same dataset.
Observable Interactivity
Observable.js can also be used directly to highlight data interactively without stringing along different r packages.
Actual Content:
Put actual ideas for content here.
1. SSP Scenario Comparison
CMIP6 scenario projections for the Northeastern US:
In the research presented here, we used future sea surface
and bottom temperature data from multiple global climate
models run under two scenarios reflecting low (SSP1-2.6) and
high greenhouse gas emissions (SSP5-8.5). A prediction
ensemble of many model runs was prepared for each
scenario.
The chart below shows the projected SST for the Northeast
U.S. region as a whole. The breadth of uncertainty between
model runs can be seen in the prediction range when taking
the 5th and 95th percentiles of the model runs used in each
ensemble.
The projected Oceanographic responses under these scenarios
and their uncertainties begin to diverge by mid-century
(2040-2069), but the differences are most apparent at the
end of the century (2070-2099).
2. Observed & Projected Environmental Change from SSP5 8.5
CMIP6 scenario projections for the Northeastern US:
These climate ensembles contain estimates of temperature
and salinity conditions at monthly intervals projected
out through 2100. Estimates are based on decades of
scientific observations in the region and projected
forward using physics-based oceanographic models.
These models are then fed data on expected GHG
emissions and climate sensitivity to those emissions
unique to each SSP scenario to see how the physical
environment responds under those assumptions.
These estimates are then used to set reasonable expectations,
and test our understanding around the projected changes
to the region's environment. Differences between scenarios and
their uncertainties highlight how much/little change we
might anticipate dependent on choices made on emissions.
The chart below displays the projected change in sea surface
temperature for the Northeast US Continental Shelf Region, based
on the shared socioeconomic emissons pathway SSP5 8.5,
an ensemble climate scenario.
2b. Observed and Projected, Both Scenarios
3. Baseline Environmental Conditions of the Recent Climate
Environmnetal Change History of the Northeastern US:
In the Northeast US the physical marine environment changes
at scales ranging from the hourly to decadal scales.
The marine environment is dynamic and inter-annual variation
is normal and expected regardless of climate change impacts.
By taking several decades of data to use as a baseline,
scientists can measure the degree that each variable
fluctuates naturally, and set benchmarks from which
to compare against.
4. Observed Species Distribution: Modern Climate
Haddock Preferences Have Determined Historic Species Distribution
With a preference for cooler water, haddock have historically been more numerous in the Gulf of Maine, becomin less numerousfurther to the South.
For comparisons against projected future climates, we've used the ten-year period of 2010-2019 as a baseline from which to measure changes.
The following map below displays how our species distribution model allocates haddock biomass density when given the average environmental conditions of that 2010-2019 period. This is how we understand haddock abundance/biomass to be distributed currently under the average environmental conditions of recent years.
5. Projected Distribution: Change in a +1C Climate
Habitat Preference-Based Species Distribution Changes
Based on the projected environment of the SSP5 8.5 climate ensemble. Haddock distributions are projected
to decline in the southern parts of their range, and increase North of Georges Bank and along the Scotian Shelf.
These projected changes raise a number of ecological and fisheries management considerations.
Changes in distribution driven by shifts in the local climate will change the vulnerability of
haddock to fishing pressure and add complexity to stock the assesment process.
These habitat-driven distribution shifts will also need to be balanced against
the ecological and life-history needs for the species. Historical distribution patterns that
emerged with the purposes of capitalizing on prey availability and/or
predator evasion will encounter tradeoffs with changing physical habitat preferences.
6. Observed Species Environmental Preferences
Gulf of Maine Haddock Preferences Facing Projected Climates:
Haddock is an important fish species found in the cooler waters
off the Coast of New England. They serve an important role ecologically
and they support a regional fishery and commonly eaten as
fried fish fillets.
Leveraging over 50 years of NOAA Survey data,
scientists can quantify the relationship between haddock abundance
and the temperatures where they are caught. When average
temperatures from projected climates
are overlayed, we can see whether conditions
are more/less favorable with respect to those
preferences.
Leveraging over 50 years of NOAA Survey data,
scientists can quantify the relationship between haddock abundance
and the temperatures where they are caught. When average
temperatures from projected climates
are overlayed, we can see whether conditions
are more/less favorable with respect to those
preferences.
7. Region-Specific Seasonal Outlooks
US Area Maps
For COCA we only really need the US area, so maybe clip to that area:
